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bioRxiv2026

Structural and Metabolic Characterization of Ni(I)-inhibitors Provide a Robust Anti-Methanogenicity Scoring System

Atmospheric methane (CH4) acts as a key contributor to global warming and a short-lived climate forcer. CH4 mitigation represents the most promising means to address short-term climate change. Ruminant enteric CH4 produced by methanogenic archaea represents 27.2% of global CH4 emissions. Only a few of the direct methanogenesis inhibitors identified bear high mitigation potential hence it is important to investigate their underlying modes of action. Here, we elucidated biophysical and thermodynamic interplay between known inhibitors and cofactor F430, to determine their stoichiometric ratios and binding affinities. We leverage this prior in a robust contrastive learning approach to functionally cluster known sixteen inhibitors and 53,959 bovine-linked metabolites. We demonstrate a multi-factor optimization protocol to identify putative inhibitors with: (i) high bacterial membrane permeability, (ii) no adverse effect to ruminal fermentation, (iii) known degradation pathway, and (iv) direct commercial availability. Subsequent in vitro assays and community metabolic modeling with a first set of eight treatment molecules revealed structo-metabolic priors that tie thermodynamic signatures of inhibition to metabolic flux shifts. We established a multi-scale workflow that transforms ostensibly negative compounds into mechanistic insight, linking rumen metabolic flux shifts to MCR-F430-Ni(I) inhibition chemistry as a foundation for rational methane-mitigation design. COVER ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=147 SRC="FIGDIR/small/708075v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1d38d21org.highwire.dtl.DTLVardef@1d681d9org.highwire.dtl.DTLVardef@1e70c0corg.highwire.dtl.DTLVardef@1c8223f_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2025

Improved Functional Classification of Hydrolases through Pairwise Structural Similarity of Reaction Cores

We report a systematic pipeline is for extracting the catalytically relevant reactive site in addition to the surrounding allosterically linked residue shells around the reaction site of the most diverse enzyme class - hydrolases, with known experimental structures. We first successfully extract 40196 such hydrolase reaction cores (RC) and collates them into a publicly accessible reaction core collection (RC-Hydrolase). We perform 128M pairwise shape comparison across RC-Hydrolase using a three-dimensional search engine and present 155,329 pair instances clustering them by 60% or higher similarities in a publicly available, visually interactive dataset. Robustness of defined RCs is shown to successfully capture experimentally known function-enhancing mutations distal to the active site in PETases. Allowing comparisons of enzyme reaction centers across functional spaces (ligands bound, EC classification numbers, and expression hosts) enables identification of enzyme backbones which can be minimally mutated to accommodate more than one type of catalytic activity thereby aiding rational design of multifunctional enzymes. We also demonstrate how such versatile enzyme backbones could be leveraged by the latest diffusion-based protein design models to design bespoke libraries of small molecule inhibitors, and structurally stable multifunctional enzyme pockets. With only sporadic successes in multifunctional enzyme design thus far, we provide strong structural priors for machine-learning-guided advanced enzyme engineering in the future.

bioinformatics↗